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Autonomous Shepherding Behaviors of Multiple Target Steering Robots

This paper presents a distributed coordination methodology for multi-robot systems, based on nearest-neighbor interactions. Among many interesting tasks that may be performed using swarm robots, we propose a biologically-inspired control law for a shepherding task, whereby a group of external agents...

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Detalles Bibliográficos
Autores principales: Lee, Wonki, Kim, DaeEun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751650/
https://www.ncbi.nlm.nih.gov/pubmed/29186836
http://dx.doi.org/10.3390/s17122729
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author Lee, Wonki
Kim, DaeEun
author_facet Lee, Wonki
Kim, DaeEun
author_sort Lee, Wonki
collection PubMed
description This paper presents a distributed coordination methodology for multi-robot systems, based on nearest-neighbor interactions. Among many interesting tasks that may be performed using swarm robots, we propose a biologically-inspired control law for a shepherding task, whereby a group of external agents drives another group of agents to a desired location. First, we generated sheep-like robots that act like a flock. We assume that each agent is capable of measuring the relative location and velocity to each of its neighbors within a limited sensing area. Then, we designed a control strategy for shepherd-like robots that have information regarding where to go and a steering ability to control the flock, according to the robots’ position relative to the flock. We define several independent behavior rules; each agent calculates to what extent it will move by summarizing each rule. The flocking sheep agents detect the steering agents and try to avoid them; this tendency leads to movement of the flock. Each steering agent only needs to focus on guiding the nearest flocking agent to the desired location. Without centralized coordination, multiple steering agents produce an arc formation to control the flock effectively. In addition, we propose a new rule for collecting behavior, whereby a scattered flock or multiple flocks are consolidated. From simulation results with multiple robots, we show that each robot performs actions for the shepherding behavior, and only a few steering agents are needed to control the whole flock. The results are displayed in maps that trace the paths of the flock and steering robots. Performance is evaluated via time cost and path accuracy to demonstrate the effectiveness of this approach.
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spelling pubmed-57516502018-01-10 Autonomous Shepherding Behaviors of Multiple Target Steering Robots Lee, Wonki Kim, DaeEun Sensors (Basel) Article This paper presents a distributed coordination methodology for multi-robot systems, based on nearest-neighbor interactions. Among many interesting tasks that may be performed using swarm robots, we propose a biologically-inspired control law for a shepherding task, whereby a group of external agents drives another group of agents to a desired location. First, we generated sheep-like robots that act like a flock. We assume that each agent is capable of measuring the relative location and velocity to each of its neighbors within a limited sensing area. Then, we designed a control strategy for shepherd-like robots that have information regarding where to go and a steering ability to control the flock, according to the robots’ position relative to the flock. We define several independent behavior rules; each agent calculates to what extent it will move by summarizing each rule. The flocking sheep agents detect the steering agents and try to avoid them; this tendency leads to movement of the flock. Each steering agent only needs to focus on guiding the nearest flocking agent to the desired location. Without centralized coordination, multiple steering agents produce an arc formation to control the flock effectively. In addition, we propose a new rule for collecting behavior, whereby a scattered flock or multiple flocks are consolidated. From simulation results with multiple robots, we show that each robot performs actions for the shepherding behavior, and only a few steering agents are needed to control the whole flock. The results are displayed in maps that trace the paths of the flock and steering robots. Performance is evaluated via time cost and path accuracy to demonstrate the effectiveness of this approach. MDPI 2017-11-25 /pmc/articles/PMC5751650/ /pubmed/29186836 http://dx.doi.org/10.3390/s17122729 Text en © 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lee, Wonki
Kim, DaeEun
Autonomous Shepherding Behaviors of Multiple Target Steering Robots
title Autonomous Shepherding Behaviors of Multiple Target Steering Robots
title_full Autonomous Shepherding Behaviors of Multiple Target Steering Robots
title_fullStr Autonomous Shepherding Behaviors of Multiple Target Steering Robots
title_full_unstemmed Autonomous Shepherding Behaviors of Multiple Target Steering Robots
title_short Autonomous Shepherding Behaviors of Multiple Target Steering Robots
title_sort autonomous shepherding behaviors of multiple target steering robots
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5751650/
https://www.ncbi.nlm.nih.gov/pubmed/29186836
http://dx.doi.org/10.3390/s17122729
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